Since the beginning of time companies of all shapes and sizes have been collecting data from various sources, attempting to correlate them into seeing a single source of truth on their customer. The messy and chaotic process usually looks something like this:

Get a data feed from a Web Analytics tool for clickstream data

Export data from various systems of record including CRM, Loyalty, POS and Call Center

Bring all of that data into a Data Warehouse/Lake

Begin looking for ways to ‘match’ that data up table by table in a very manual way

Correlate the data into a record based system with the sole purpose of gaining a ‘Single View of the Customer’

Run reports, gain insights and ‘maybe’ even export lists of customers to marketing systems

This process is extremely painful because the usual state of data is stale at best and lacks any agility whatsoever. The core reason why this process hurts so much is that the correlation happens after the fact in post-process formatting. Welcome to the wonderful world of data silos.

Lucky for you there is a much better and more streamlined way to achieve the ever elusive single customer view. And the most important place to start this process is at the point of data collection – before data even has a chance of living in a silo.

Here are 5 key steps to achieving a single view of the customer through data orchestration:

Establish a company wide Data Layer strategy so that all data being collected follows a standard nomenclature.

Integrate a data collection footprint across every single customer touchpoint including web, mobile, CRM, POS, Call Center, Kiosk and anywhere else customer data will be created

Leverage a real-time solution that connects enterprise applications that collect, correlate, stitch and enrich data in flight – rather than after the fact.

Create rules within that solution that will make decisions about when to trigger actions across the entire MarTech stack

Simultaneously sync this data into a Data Warehouse/Lake

In this more modern approach the Data Warehouse/Lake is at the end of the process and also receives the real time output from the platform incredibly fast.

Now the data that is being analyzed is exactly the same as the data that is being activated.

Yes the devil is in the details but this is a key change in overall data orchestration, which will drive true digital transformation.

Jay Calavas has more than 15 years of proven digital marketing experience, and is responsible for helping promote the global adoption of the Tealium brand and products. Prior to this role, Jay first ran global sales at Tealium, helping grow the company into the market leader for enterprise tag management. After that he orchestrated the global launch of AudienceStream, the first real-time segmentation and action engine designed for marketers. Before Tealium, Jay provided his leadership skills across the digital marketing ecosystem with companies such as ExactTarget, TouchCommerce, Visual Sciences and WebSideStory (now Adobe Systems). Jay studied marketing and finance at James Madison University.

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